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How big data is changing Renewable Energy

Rhiannah Slamaker our consultant managing the role
Published on 9 August 2022

Big data and data science have been used by the energy sector for years, however, as we enter a new digital era, its impact on renewable energy is set to grow exponentially. As clean energy becomes more of a viable choice for organisations, data professionals are taking up renewable energy jobs in order to have more of an influence on processes within the sector.

 It is projected that clean energy will form 50% of all energy sources by 2050 and big data in the clean energy industry can be used to optimise and improve operations. As such, the fields of data science and data analytics stand to play a significant role in the future of energy.

 Here, we take a look at how big data is changing the renewable energy sector and what that means for the future. 


Improving energy efficiency

Your renewable energy business can benefit significantly from data science. As the technology involved in sensors and networking increases, more data will become available, giving data scientists more leverage to inform on efficiency. 

To increase efficiency at a solar or wind farm, for instance, it may be necessary to make adjustments to daily operations which can be identified using data. Additionally, with the cost of renewables in steep decline due to technological advancements, the ability to get more mileage out of your solar plant or wind farm is now more desirable than ever. 

As the threat of climate change increases and fossil fuel resources become more unstable, many organisations will be looking for alternative energy sources. If data can continue to improve the efficiency of clean energy, then the renewable sector can expect a significant spike in popularity. 

 

Predicting weather patterns

In recent years, data science has been used to forecast the supply of energy based on typical weather behaviour and to monitor the condition of solar panels. For instance, solar energy is one of the most popular forms of renewable energy and it is still expanding. However, it is reliant on sunshine, a transient natural resource. As a result, the ability to estimate power generation is essential for integrating solar photovoltaics into conventional electrical grid systems. 

Thanks to the combination of big data, predictive analytics, and machine learning, weather and satellite data can now be combined to give accurate predictions of weather patterns. Additionally, getting more use out of your solar power, bioenergy sources and more is now more attractive than ever given the rapid drop in the cost of renewable energy as a result of technological improvements.

 

Reducing production costs

Renewable energy is enjoying a significant increase in support and much of this has been attributed to the gradual decline in its production cost. According to studies, the price of building an offshore wind farm has fallen across the globe and the general production costs within the clean energy sector have reduced dramatically. 

Companies that use renewable energy can now create more energy without incurring additional infrastructure costs thanks to the most recent big data and predictive analysis technologies. 

One of the factors contributing to the steady drop in the cost of renewable energy is the ever-increasing capacity to extract relevant information from big data. This information is used to identify waste and unnecessary expenses in production costs.

 

Attracting investment

Though the renewable energy sector is showing remarkable signs of expansion, the growth could be improved if the sector could attract further investment. Only a small number of private investors such as banks, insurance firms, and financial institutions now view renewable energy projects as reliable investment opportunities. 

Most investors are usually reluctant to finance a renewable energy initiative since there is typically a lack of trustworthy evidence that supports the project's long-term profitability.

With big data tools, companies can produce more accurate forecasts on energy generation based on past performance. It can also help determine the exact number of wind turbines, solar panels or other equipment needed to produce the required energy. 

Thus, businesses can use big data to make renewable energy projects more appealing for investment.


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